How Microsoft Uses AI for Threat Intelligence & Malware Analysis
What if the prompts used in your AI systems were treated as a new class of threat indicator? In this episode, Thomas Roccia, Senior Security Researcher at Microsoft, introduces the concept of the IOPC (Indicator of Prompt Compromise), sharing that "when there is a threat actors using a GenAI model for malicious activities, then the prompt... is considered as an IOPC".
The conversation dives deep into the practical application of AI in threat intelligence. Thomas shares details from his open-source projects, including NOVA, a tool for detecting adversarial prompts, and an AI agent he built to track the complex money laundering scheme from a $1.4 billion crypto hack . We also explore how AI is dramatically lowering the barrier to entry for complex tasks like reverse engineering, turning a once-niche skill into something accessible to a broader range of security professionals .
Questions asked:
00:00 Introduction
02:20 Who is Thomas Roccia?
03:20 Using AI for Reverse Engineering & Malware Analysis
04:30 Building an AI Agent to Track Crypto Money Laundering
11:30 What is an IOPC (Indicator of Prompt Compromise)?
14:40 MITRE ATLAS: A TTP Framework for LLMs
18:20 NOVA: An Open-Source Tool for Detecting Malicious Prompts
23:15 Using RAG for Threat Intelligence on Data Leaks
31:00 Proximity: A New Scanner for Malicious MCP Servers
34:30 Why Good Ideas are Now More Valuable Than Execution
35:30 Real-World AI Threats: Stolen API Keys & Smart Malware
40:15 The Challenge of Building Reliable Multi-Agent Systems
48:20 How AI is Lowering the Barrier for Reverse Engineering
50:30 "Vibe Investigating": Assisting the SOC with AI
54:15 Caleb's Personal AI Agent for Document Organization
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